code: def demo_recs():
      """
      A demo set of train, test, and recommendation data.
      """
      train, test = simple_test_pair(ml_test.ratings, f_rates=0.5)
  
      users = test["user"].unique()
      algo = PopScore()
      algo = PlackettLuce(algo, rng_spec="user")
      algo.fit(train)
  
      recs = recommend(algo, users, 500)
      return train, test, recs
  
file_path: lkpy/lenskit/util/test.py
imports: import os
  import os.path
  from contextlib import contextmanager
  import pytest
  from lenskit.datasets import MovieLens, ML100K
  from lenskit.crossfold import simple_test_pair
  from lenskit.algorithms.basic import PopScore
  from lenskit.algorithms.ranking import PlackettLuce
  from lenskit.batch import recommend
label_desc: Use image node_id 1 for calling a global function with example usage: demo_recs() and returns: train,  test,  recs